Reads in dataframe of Promega data, and normalise.

This function assumes that the left most row is cell/negative control, and second column from the left as virus/positive control.

Usage

normalise(
  df,
  control_neg_column = c(1),
  control_pos_column = c(2),
  control_plating = "column",
  control_neg_wells = c("A1", "B1", "C1", "D1", "E1", "F1", "G1", "H1"),
  control_pos_wells = c("A2", "B2", "C2", "D2", "E2", "F2", "G2", "H2"),
  cluster = FALSE,
  filename = ""
)

Arguments

df: dataframe to normalise, where left most column is negative control, and second left column is positive control.
control_neg_column: The column(s) which negative/cell control are located (column number from left, integer)
control_pos_column: The column(s) which positive/virus control are located (column number from left, integer)
control_plating: how the controls are plated. default = "column", set to "custom" to input by wells using control_neg_wells and control_pos_wells.
control_neg_wells: The wells which negative control are located (custom mode)
control_pos_wells: The wells which positive control are located (custom mode)
cluster: Experimental feature - uses k-means clustering to detect and exclude anomalies in negative and positive control (default = FALSE)

Value

A normalised dataframe where negative and positive control columns are removed.